You do realize that one reason for the current state of affairs is the complete lack of ability to test ANY new theory? The LHC was really only designed to see what we expected to see. If we don't see some things that will be great but it will mean that the Standard Model is pretty much wrong. But we won't be able to test anything else.
It is naive to believe that everything in the world can be optimized my some market solution. If some group isn't producing results it is not always the case that reducing their funding will produce better results (e.g. education and basic science). We have trained many great theoretical physicists in the past 30 years but have invested very little in experiments that are likely to produce that could falsify any modern theory.
I am in astrophysics so....
Regardless I think there is a very real difference between fields where you can leave your experiment on and grow significance with square root time and those that you simply cannot. It is not a matter of difficulty but a matter of biology. One cannot study many disease with the quantity of data to make a robust statistical conclusion. Biomedical research needs to accept this. However simply discounting their research because you think they aren't working hard enough isn't going to change anything.
I agree with your general tone and statement. However it is important to note the inherent limitations of biomedical research. Generally one CANNOT do large scale studies needed to get a statistically robust result. All of physics and astrophysics generally use the 5 sigma discover requirement which means you have to measure the effect to 3e-7. You cannot do this with people as subjects. It is hard to do this with ANY biological subject. Many of the issues brought up stem from this.
I think much of the problem is exacerbated by the public-or-perish mentality but is even more affected by the total lack of reporting null results (when you DO NOT see anything). This skews your overall distribution. It is like not accounting for trials (because you aren't). In biomedical research they need to spend more time quantifying their trials and placing their results in the proper statistical context. Just staying that you are less likely to get parkinson's disease if you drink coffee because we asked a bunch of people isn't the whole story. How many questions did you ask? Was it 100? Did you treat all those as essentially trials?
Somebody ought to cross ball point pens with coat hangers so that the pens will multiply instead of disappear.